Characterization of zebrafish mutants with defects in bone calcification during development

Using the fluorescent dyes calcein and alcian blue, we stained the F3 generation of chemically (ENU) mutagenized zebrafish embryos and larvae, and screened for mutants with defects in bone development. We identified a mutant line, bone calcification slow (bcs), which showed delayed axial vertebra calcification during development. Before 4–5 days post-fertilization (dpf), the bcs embryos did not display obvious abnormalities in bone development (i.e., normal number, size and shape of cartilage and vertebrae). At 5–6 dpf, when vertebrae calcification starts, bcs embryos began to show defects. At 7 dpf, for example, in most of the bcs embryos examined, calcein staining revealed no signals of vertebrae mineralization, whereas during the same developmental stages, 2–14 mineralized vertebrae were observed in wild-type animals. Decreases in the number of calcified vertebrae were also observed in bcs mutants when examined at 9 and 11 dpf, respectively. Interestingly, by 13 dpf the defects in bcs mutants were no longer evident. There were no significant differences in the number of calcified vertebrae between wild-type and mutant animals. We examined the expression of bone development marker genes (e.g., Sox9b, Bmp2b, and Cyp26b1, which play important roles in bone formation and calcification). In mutant fish, we observed slight increases in Sox9b expression, no alterations in Bmp2b expression, but significant increases in Cyp26b1 expression. Together, the data suggest that bcs delays axial skeletal calcification, but does not affect bone formation and maturation.     

Inhibition of MAPK by prolactin signaling through the short form of its receptor in the ovary and decidua: involvement of a novel phosphatase

Prolactin (PRL) is essential for normal reproduction and signals through two types of receptors, the short (PRL-RS) and long (PRL-RL) form. We have previously shown that transgenic mice expressing only PRL-RS (PRLR(-/-)RS) display abnormal follicular development and premature ovarian failure. Here, we report that MAPK, essential for normal follicular development, is critically inhibited by PRL in reproductive tissues of PRLR(-/-)RS mice. Consequently, the phosphorylation of MAPK downstream targets are also markedly inhibited by PRL without affecting immediate upstream kinases, suggesting involvement of MAPK specific phosphatase(s) in this inhibition. Similar results are obtained in a PRL-responsive ovary-derived cell line (GG-CL) that expresses only PRL-RS. However, we found the expression/activation of several known MAPK phosphatases not to be affected by PRL, suggesting a role of unidentified phosphatase(s). We detected a 27-kDa protein that binds to the intracellular domain of PRL-RS and identified it as dual specific phosphatase DUPD1. PRL does not induce expression of DUDP1 but represses its phosphorylation on Thr-155. We also show a physical association of this phosphatase with ERK1/2 and p38 MAPK. Using an in vitro phosphatase assay and overexpression studies, we established that DUPD1 is a MAPK phosphatase. Dual specific phosphatase inhibitors as well as siRNA to DUPD1, completely prevent PRL-mediated MAPK inhibition in ovarian cells. Our results strongly suggest that deactivation of MAPK by PRL/PRL-RS contributes to the severe ovarian defect in PRLR(-/-)RS mice and demonstrate the novel association of PRL-RS with DUPD1 and a role for this phosphatase in MAPK deactivation.     

ITMSQ: A software tool for N‐ and C‐terminal fragment ion pairs based isobaric tandem mass spectrometry quantification

Tandem MS (MS2) quantification using the series of N‐ and C‐terminal fragment ion pairs generated from isobaric‐labelled peptides was recently considered an accurate strategy in quantitative proteomics. However, the presence of multiplexed terminal fragment ion in MS2 spectra may reduce the efficiency of peptide identification, resulting in lower identification scores or even incorrect assignments. To address this issue, we developed a quantitative software tool, denoted isobaric tandem MS quantification (ITMSQ), to improve N‐ and C‐terminal fragment ion pairs based isobaric MS2 quantification. A spectrum splitting module was designed to separate the MS2 spectra from different samples, increasing the accuracy of both identification and quantification. ITMSQ offers a convenient interface through which parameters can be changed along with the labelling method, and the result files and all of the intermediate files can be exported. We performed an analysis of in vivo terminal amino acid labelling labelled HeLa samples and found that the numbers of quantified proteins and peptides increased by 13.64 and 27.52% after spectrum splitting, respectively. In conclusion, ITMSQ provides an accurate and reliable quantitative solutionfor N‐ and C‐terminal fragment ion pairs based isobaric MS2 quantitative methods.     

Impact of nonrandom selection mechanisms on the causal effect estimation for two-sample Mendelian randomization methods

Nonrandom selection in one-sample Mendelian Randomization (MR) results in biased estimates and inflated type I error rates only when the selection effects are sufficiently large. In two-sample MR, the different selection mechanisms in two samples may more seriously affect the causal effect estimation. Firstly, we propose sufficient conditions for causal effect invariance under different selection mechanisms using two-sample MR methods. In the simulation study, we consider 49 possible selection mechanisms in two-sample MR, which depend on genetic variants (G), exposures (X), outcomes (Y) and their combination. We further compare eight pleiotropy-robust methods under different selection mechanisms. Results of simulation reveal that nonrandom selection in sample II has a larger influence on biases and type I error rates than those in sample I. Furthermore, selections depending on X+Y, G+Y, or G+X+Y in sample II lead to larger biases than other selection mechanisms. Notably, when selection depends on Y, bias of causal estimation for non-zero causal effect is larger than that for null causal effect. Especially, the mode based estimate has the largest standard errors among the eight methods. In the absence of pleiotropy, selections depending on Y or G in sample II show nearly unbiased causal effect estimations when the casual effect is null. In the scenarios of balanced pleiotropy, all eight MR methods, especially MR-Egger, demonstrate large biases because the nonrandom selections result in the violation of the Instrument Strength Independent of Direct Effect (InSIDE) assumption. When directional pleiotropy exists, nonrandom selections have a severe impact on the eight MR methods. Application demonstrates that the nonrandom selection in sample II (coronary heart disease patients) can magnify the causal effect estimation of obesity on HbA1c levels. In conclusion, nonrandom selection in two-sample MR exacerbates the bias of causal effect estimation for pleiotropy-robust MR methods.     

Auto-adaptive Alpha Allocation: A Strategy to Mitigate Risk on Study Assumptions

In some clinical development programs, there are potential biomarkers with promising but uncertain predictive effect, while the probability of success in the overall population cannot be readily dismissed. It is risky to focus only on the overall population, or just the biomarker subpopulation. In 2009, Chen and Beckman proposed a Bayesian decision framework to optimize the type I error rate (alpha) allocation in a Phase III clinical study with possible predictive subset effect. The utilization of internal data in this framework is of particular interest because it provides an opportunity to mitigate the potential risk of misspecified study assumptions using an auto-adaptive strategy. In this paper, we examine this auto-adaptive strategy in detail through extensive numerical case studies and provide guidance on the appropriate use of partial current trial (internal) data in this data-driven optimization framework. We show that internal data can be used to inform the alpha allocation to hypothesis testing in the overall population and the subgroup. The resulting adaptive testing strategy is robust with respect to the uncertainty in the predictive subgroup effect and biomarker prevalence.     

Soluble expression, purification and functional identification of a disulfide-rich conotoxin derived from Conus litteratus

Conotoxins are a diverse array of small peptides mostly with multiple disulfide bridges. These peptides become an increasing significant source of neuro-pharmacological probes and drugs as a result of the high selectivity for ion channels and receptors. Usually, the analogue of natural conotoxins is produced by means of chemical synthesis. Here, we present a simple and fast strategy of producing disulfide-rich conotoxins via recombinant expression. By fused with thioredoxin and His tag, a novel O-superfamily conotoxin lt7a was successfully expressed in Escherichia coli and purified, resulting in a high yield of recombinant lt7a about 6 mg/l. The purity of target protein is up to 95% as identified by HPLC results. Whole cell patch-clamp recording revealed that the new conotoxin blocked voltage-sensitive sodium channels in rat dorsal root ganglion neurons, indicating it might be a novel microO-conotoxin.     

Effects of caffeine on in vivo and in vitro oocyte maturation in mice

The objective was to investigate, using a mouse model, the effects of caffeine on the number of ovulated oocytes, the rate of oocyte maturation, the susceptibility of oocytes to activating stimuli, spindle morphology, and distribution of cortical granules (CGs). Mice were given caffeine (150 mg/kg body weight ip) at various times relative to hCG (-2, 0, and +2h); in an in vitro study, 1, 5 or 10 mM caffeine was added to the maturation culture. Caffeine had no effect on the quality of oocytes in vivo maturation, but caffeine was detrimental to the quality of oocytes matured in vitro. Further studies are needed to determine caffeine concentration in follicles relative to that in culture medium.